class_docstr: A specific binarization of the MNIST dataset.
docstr: Returns SplitGenerators.
docstr_tok: ["Returns","SplitGenerators","."]
code: def _split_generators(self, dl_manager):
      """Returns SplitGenerators."""
      filenames = {
          "train_data": _TRAIN_DATA_FILENAME,
          "validation_data": _VALID_DATA_FILENAME,
          "test_data": _TEST_DATA_FILENAME,
      }
      files = dl_manager.download(
          {
              k: urllib.parse.urljoin(_URL, v)
              for k, v in filenames.items()
          }
      )
  
      return [
          tfds.core.SplitGenerator(
              name=tfds.Split.TRAIN,
              gen_kwargs=dict(
                  data_path=files["train_data"],
              ),
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.VALIDATION,
              gen_kwargs=dict(
                  data_path=files["validation_data"],
              ),
          ),
          tfds.core.SplitGenerator(
              name=tfds.Split.TEST,
              gen_kwargs=dict(
                  data_path=files["test_data"],
              ),
          ),
      ]
  
file_path: datasets/tensorflow_datasets/datasets/binarized_mnist/binarized_mnist_dataset_builder.py
imports: import numpy
  from six.moves import urllib
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  from tensorflow_datasets.image_classification import mnist
  import tensorflow_datasets.public_api
label_desc: Use image node_id 2 for calling the Builder obj's underlying member method code with example usage: obj._split_generators(dl_manager) and returns: list